Measurement of neutral strange particle production in the
underlying event in proton-proton collisions at s = 7TeV
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Citation
Chatrchyan, S., V. Khachatryan, A. M. Sirunyan, A. Tumasyan,
W. Adam, T. Bergauer, M. Dragicevic, et al. “Measurement of
neutral strange particle production in the underlying event in
proton-proton collisions at s = 7TeV .” Physical Review D 88, no.
5 (September 2013). © 2013 CERN, for the CMS Collaboration
As Published
http://dx.doi.org/10.1103/PhysRevD.88.052001
Publisher
American Physical Society
Version
Final published version
Accessed
Thu May 26 06:47:17 EDT 2016
Citable Link
http://hdl.handle.net/1721.1/84706
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Detailed Terms
PHYSICAL REVIEW D 88, 052001 (2013)
Measurement of neutral strange particle production
in the underlying event in
pffiffiffi
proton-proton collisions at s ¼ 7 TeV
S. Chatrchyan et al.*
(CMS Collaboration)
(Received 26 May 2013; published 3 September 2013)
Measurements are presented of the production of primary KS0 and particles in proton-proton
pffiffiffi
collisions at s ¼ 7 TeV in the region transverse to the leading charged-particle jet in each event. The
average multiplicity and average scalar transverse momentum sum of KS0 and particles measured at
pseudorapidities jj < 2 rise with increasing charged-particle jet pT in the range 1–10 GeV=c and
saturate in the region 10–50 GeV=c. The rise and saturation of the strange-particle yields and transverse
momentum sums in the underlying event are similar to those observed for inclusive charged particles,
which confirms the impact-parameter picture of multiple parton interactions. The results are compared to
recent tunes of the PYTHIA Monte Carlo event generator. The PYTHIA simulations underestimate the data
by 15%–30% for KS0 mesons and by about 50% for baryons, a deficit similar to that observed for the
inclusive strange-particle production in non-single-diffractive proton-proton collisions. The constant
strange- to charged-particle activity ratios with respect to the leading jet pT and similar trends for mesons
and baryons indicate that the multiparton-interaction dynamics is decoupled from parton hadronization,
which occurs at a later stage.
DOI: 10.1103/PhysRevD.88.052001
PACS numbers: 12.38.Aw, 13.85.Ni
I. INTRODUCTION
This paper describes a measurement of the production of
baryons in the underprimary KS0 mesons, and and lying event in proton-proton (pp) collisions at a center-ofmass energy of 7 TeV with the Compact Muon Solenoid
(CMS) detector at the Large Hadron Collider (LHC).
In the presence of a hard process, characterized by particles or clusters of particles with large transverse momentum
pT with respect to the beam direction, the final state of
hadron-hadron interactions can be described as the superposition of several contributions: the partonic hard scattering, initial- and final-state radiation, additional ‘‘multiple
partonic interactions’’ (MPI), and ‘‘beam-beam remnants’’
(BBR) interactions. The products of initial- and final-state
radiation, MPI and BBR, form the ‘‘underlying event’’ (UE).
In this paper, the UE properties are analyzed with reference to the direction of the highest-pT jet reconstructed
from charged primary particles (leading charged-particle
jet). This leading jet is expected to reflect the direction of the
parton produced with the highest transverse momentum in
the hard interaction. Three distinct topological regions in
the hadronic final state are defined in terms of the azimuthal
angle between the directions of the leading jet and that
of any particle in the event. Particle production in the
‘‘toward’’ region, jj < 60 , and in the ‘‘away’’ region,
*Full author list given at the end of the article.
Published by the American Physical Society under the terms of
the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and
the published article’s title, journal citation, and DOI.
1550-7998= 2013=88(5)=052001(21)
jj>120 , is expected to be dominated by the hard
parton-parton scattering. The UE structure can be best
studied in the ‘‘transverse’’ region, 60 <jj<120 [1,2].
Studies of the UE activity in charged primary particles in
proton-proton collisions at different center-of-mass energies have been published by the ATLAS [3] and CMS
[1,4,5] collaborations. Observables such as the average
multiplicity of charged primary particles per event, hereafter referred to as ‘‘average rate,’’ and the average scalar
sum of primary particle pT per event, hereafter referred to
as ‘‘average pT sum,’’ have been measured in the transverse region. These quantities exhibit a steep rise with
increasing charged-particle jet pT up to a value that
depends on the proton-proton center-of-mass energy
(around 10 GeV=c for pp collisions at 7 TeV), followed
by a slow rise. Within the MPI framework, a hard jet is likely
to be produced in collisions with a small impact parameter
between the colliding protons, consequently resulting in
large MPI activity [6,7]. The MPI activity saturates at values
of the hard scale typical of central collisions.
The present analysis considers identified neutral strange
as additional probes to study the
particles (KS0 , , and )
baryon
underlying event. Unless stated otherwise, and data are merged and referred to as baryon data. The
production of primary KS0 and particles in the transverse
pffiffiffi
region at s ¼ 7 TeV is studied as a function of the scale
of the hard process. Fully corrected average rates and pT
sums of primary KS0 mesons and baryons, as well as
ratios to the charged primary-particle rates and pT sums,
are compared to simulations. This analysis complements
the studiespof
ffiffiffi strangeness production in minimum-bias
events at s ¼ 7 TeV published by the ALICE [8,9],
052001-1
Ó 2013 CERN, for the CMS Collaboration
S. CHATRCHYAN et al.
PHYSICAL REVIEW D 88, 052001 (2013)
ATLAS [10], and CMS [11] collaborations. Comparisons
of nonsingle diffractive data [11] with predictions made
with the PYTHIA 6 [12] and PYTHIA 8 [13] Monte Carlo
event generators have shown that the latter largely under0
estimate the data, e.g.,
pffiffiby
ffi 30% for KS production and 50%
for production at s ¼ 7 TeV for PYTHIA 6 tune D6T
[2,14], with little improvement for more recent tunes.
The simulations are performed with versions of PYTHIA
that include MPI. The most recent versions have been
tuned to reproduce the UE activity observed with primary
charged particles at the LHC at 0.9 TeV and 7 TeV centerof-mass energies. The parameters describing strangeness
production, however, have not been tuned to LHC data yet.
All Monte Carlo samples used in this paper have been
generated with the default values of these parameters.
Recent literature [15–17] discussing the tuning of the
strangeness suppression parameters in commonly available
generators is limited. A tuning of the PYTHIA 6 parameters
to LEP, SLAC Linear Collider, and Tevatron data performed with the PROFESSOR program [15] produced bestfit parameters in disagreement with the current PYTHIA
default parameters. The resulting predicted strange meson
and baryon production rates given in the Appendix of
Ref. [15], however, do not agree well with the data used
for the tuning. Other attempts to describe strange-particle
production in pp collisions are discussed in Refs. [16,17].
The present paper focuses on the comparison with PYTHIA.
The outline of this paper is the following. In Sec. II, the
experimental conditions are described, along with the data
sets, the simulation, and the analysis technique. In Sec. III,
the systematic uncertainties are summarized. The results
are discussed in Sec. IV, and conclusions are drawn in
Sec. V.
II. EXPERIMENTAL SETUP, DATA SETS,
AND DATA ANALYSIS
The central feature of CMS is a superconducting solenoid of 6 m internal diameter. Within the superconducting
solenoid volume are a silicon pixel and strip tracker, a lead
tungstate crystal electromagnetic calorimeter, and a brass
and scintillator hadron calorimeter. Muons are measured in
gas-ionization detectors embedded in the flux-return yoke.
Extensive forward calorimetry complements the coverage
provided by the barrel and endcap detectors. CMS uses a
right-handed coordinate system, with the origin at the
nominal interaction point, the x axis pointing to the center
of the LHC, the y axis pointing up (perpendicular to the
LHC plane), and the z axis along the anticlockwise-beam
direction. The polar angle is measured from the positive
z axis, and the azimuthal angle is measured in the
x y plane. The tracker measures charged particles
within the pseudorapidity range jj < 2:5, where ¼
ln ðtan ð=2ÞÞ. It consists of 1440 silicon pixel and
15 148 silicon strip detector modules and is located in the
3.8 T field of the superconducting solenoid. For the
charged particles of interest in this analysis, the transverse
momentum resolution is relatively constant with pT , varying from 0.7% at ¼ 0 to 2% at jj ¼ 2. The transverse
and longitudinal impact-parameter resolutions, d0 and
dz , respectively, depend on pT and on , ranging from
d0 ¼400m and dz ¼1000m at pT ¼ 0:3 GeV=c and
jj > 1:4 to d0 ¼ 10 m and dz ¼ 30 m at pT ¼
100 GeV=c and jj < 0:9. A more detailed description of
the CMS detector can be found in Ref. [18].
A. Event selection, data sets, and
Monte Carlo simulation
The event selection is identical to the one described in
[1], unless explicitly stated otherwise. Minimum-bias
events were triggered by requiring coincident signals in
beam scintillator counters located on both sides of the
experiment and covering the pseudorapidity range 3:23 <
jj < 4:65, and in the beam pickup devices [18]. Events
were then recorded with a prescaled trigger requiring the
presence of at least one track segment in the pixel detector
with pT > 200 MeV=c. The trigger conditions are applied
to both data and simulated samples. The trigger efficiency
for the events selected in the analysis is close to 100%, and
no bias from the trigger selection is found.
The data used in this analysis were collected in early
2010 when pileup (multiple pp collisions per proton bunch
crossing) was very low. Selected events are required to
contain a single reconstructed primary vertex, a condition
that rejects about 1% of the events satisfying all the other
selection criteria. The primary vertex is fit with an adaptive
algorithm [19] and must have at least four tracks, a transverse distance to the beam line smaller than 2 cm, and a z
coordinate within 10 cm of the nominal interaction point.
Events are required to contain a track jet with reconstructed pT > 1 GeV=c and jj < 2. Track jets are reconstructed from the tracks of charged particles, with the
anti-kT algorithm [20,21] and a clustering radius R ¼
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
0:5, where R¼ ðÞ2 þðÞ2 . The tracks are required
to be well reconstructed, to have pT > 500 MeV=c, jj <
2:5, and to be consistent with originating from the primary
vertex. More details on the track selection can be found in
[1]. The reconstructed track jet pT is the magnitude of the
vector sum of the transverse momenta of the tracks in the
jet. The leading track jet pT is corrected for detector
response (track finding efficiency and pT measurement)
with detailed simulations based on GEANT4 [22], which
have been extensively validated with data [23–25]. This
correction is approximately independent of the track jet pT
and , and its average value is 1.01. The leading corrected
track jet is referred to as the leading charged-particle jet.
The PYTHIA versions we consider all include MPI. The
tunes used are the PYTHIA 6 D6T tune [2,14] and the PYTHIA
8 tune 1 [13], which have not been tuned to the LHC data,
and the PYTHIA 6 Z1 [26] and Z2 tunes. The two latter
052001-2
MEASUREMENT OF NEUTRAL STRANGE PARTICLE . . .
PYTHIA 6 tunes, as well as PYTHIA 8, include pT
ordering of
the parton showers, and a new model [27] where MPI are
interleaved with parton showering. PYTHIA 8 includes hard
diffraction in addition to the new MPI model. The parton
distribution functions used for PYTHIA 6 D6T and PYTHIA 8
tune 1 are the CTEQ6L1 and CTEQ5L sets, respectively.
The Z1 tune uses the CTEQ5L parton distribution set,
whereas Z2 is updated to CTEQ6L1 [28] and retuned to
the underlying event activity at 7 TeV from Ref. [1] with the
PROFESSOR tool [15]. The simulated data are generated with
PYTHIA 6 version 6.422 for tunes D6T and Z1, version 6.424
for tune Z2 , and version 8.135 for PYTHIA 8 tune 1.
Simulated primary stable charged particles with a proper
lifetime c > 1 cm are clustered into jets with the anti-kT
algorithm (R ¼ 0:5). The average rates and scalar pT
sums of simulated primary KS0 and particles are computed within the transverse region of the leading simulated
charged-particle jet.
A data sample of 11 106 events with at least one
charged-particle jet with pT > 1 GeV=c and jj < 2 is
analyzed. The corresponding numbers of simulated events
are 22 106 for PYTHIA 6 D6T and 5 106 for PYTHIA 6
Z1, Z2 and PYTHIA 8 tune 1. Corrections for detector
effects and background are estimated with the PYTHIA 6
D6T sample, while the modeling of the underlying event is
studied with all the tunes mentioned.
The reconstruction of the leading charged-particle jet
results in a bias in the measured average rates and pT sums
in the transverse region. The value of this bias ranges
from þ5% to þ10% for charged-particle jet pT below
10 GeV=c, and is consistent with zero for larger pT values.
It is caused by events in which the leading jet formed by
primary charged particles is not reconstructed as the leading charged-particle jet because of tracking inefficiencies,
and a subleading jet is thus reconstructed as the leading jet.
This results in a reconstructed transverse region shifted in
. The correction for this bias is obtained from the detailed
Monte Carlo simulations of the detector response described above.
The primary vertex selection causes a small overestimate of the UE strangeness activity at low charged-particle
jet pT , at most 5% for charged-particle jet pT ¼ 1 GeV=c.
This is because the requirement that at least four tracks be
associated to the primary vertex enriches the sample in
events with higher UE activity when the charged-particle
jets have very low multiplicity. This bias is corrected by
means of detailed simulations as described in Sec. III.
B. Selection of primary V 0 candidates and
analysis strategy
hereafter
The neutral strange particles KS0 , , and ,
0
generically called V s, are identified by means of their
characteristic decay topology: a flight distance of several
centimeters before decay, two tracks of opposite charge
emerging from a secondary vertex, and an invariant mass
PHYSICAL REVIEW D 88, 052001 (2013)
consistent with that of a KS0 meson or a baryon. The V 0
momentum vector is further required to be collinear with
the vector joining the primary and secondary vertices, in
order to select primary particles.
The V 0 candidates are reconstructed by the standard
CMS offline event reconstruction program [25]. Pairs of
oppositely charged tracks with at least 3 hits in the CMS
tracker and with a nonzero transverse impact parameter
with respect to the beam line are selected (the transverse
impact parameter divided by its uncertainty is required to
be larger than 1.5). Pairs of tracks with a distance of closest
approach to each other smaller than 1 cm are fit to a
common secondary vertex, and those with a vertex fit 2
smaller than 7 and a significant distance between the beam
line and the secondary vertex (transverse flight distance
divided by its uncertainty larger than 8) are retained.
Well-reconstructed V 0 candidates are selected by applying cuts on the pseudorapidity and transverse momentum
of the decay tracks (jj < 2:5, pT > 300 MeV=c), of the
V 0 candidate (jj < 2; pT > 600 MeV=c for KS0 mesons,
pT > 1:5 GeV=c for baryons), and on the V 0 transverse
flight distance (>1 cm from the beam line). A kinematic fit
is then performed on the candidates to further purify the
sample of primary strange particles. The fit includes a
secondary vertex constraint, a mass constraint, as well as
the constraint that the V 0 momentum points away from
the primary vertex. All three hypotheses (KS0 ! þ ,
! p
þ ) are tested for each candidate
! p , and and the most probable hypothesis is considered.
Candidates with a kinematic-fit probability larger than
5% are retained.
Since simulations enter in the determination of the V 0
selection efficiency and purity, a good description of the
distributions of the kinematic-fit input variables is important. The distributions of the invariant mass of the V 0
candidates for the most probable particle-type hypothesis
are shown in Fig. 1, together with the distributions of the
invariant-mass pull. The invariant-mass pull is the difference between the reconstructed mass and the accepted V 0
mass value [29], divided by the uncertainty on the reconstructed mass calculated from the decay track parameter
uncertainties. The signal and background fractions are
shown as predicted by PYTHIA 6 D6T. The backgrounds in
the KS0 sample are mostly misidentified baryons.
Backgrounds in the sample are mostly nonprimary baryons from cascade decays of and baryons, plus
contributions from misidentified KS0 mesons and converted
photons. In general, the simulation agrees with the data. As
an example, the average mass values for KS0 mesons (
baryons) are 0:4981 GeV=c2 (1:116 GeV=c2 ) in the simulation and 0:4977 GeV=c2 (1:116 GeV=c2 ) in the data; the
corresponding rms values for the mass pull distributions are
1.17 (0.512) in the simulation and 1.23 (0.531) in the data.
For KS0 candidates, the data show larger tails than the simulation at mass pull values below ( 2). The presence of a
052001-3
S. CHATRCHYAN et al.
PHYSICAL REVIEW D 88, 052001 (2013)
5
Candidates / 3 MeV/c2
10
104
103
s = 7 TeV
Data
0
Primary K
K0S
S
Misidentified V
CMS, pp,
Candidates / 1 MeV/c2
CMS, pp,
0
Other sources
102
10
0.45
0.5
Data
103
Cascade decays
Primary Λ
Misidentified V
0.55
10
mass [GeV/c2]
CMS, pp,
Λ
0
Other sources
102
1
1.08
1
0.4
104
s = 7 TeV
1.1
1.12
1.14
mass [GeV/c2]
s = 7 TeV
CMS, pp,
s = 7 TeV
104
K0S
Candidates
Candidates
104
3
10
102
10
Λ
103
102
10
1
1
-5
0
(mass - mass
5
-4
)/σmass
PDG
-2
0
(mass - mass
2
)/σmass
4
PDG
FIG. 1 (color online). Distributions of invariant mass and invariant-mass pull for the most probable particle-type hypothesis
determined by the kinematic fit. The accepted KS0 and mass values from Ref. [29] are denoted as massPDG . The black
points indicate the data. The histograms show the backgrounds (hatched: misidentified V 0 ; green: nonprimary from and cascade decays; grey: other sources) and the signal (yellow) as predicted by PYTHIA 6 D6T. The PYTHIA prediction is normalized
to the data.
similar tail in the component shown as the hatched
histogram of the simulated distribution indicates that this
excess is due to a larger contribution from misidentified
baryons in the data compared to the simulation. This is
accounted for in the background estimation as described
below.
The pointing requirement constrains the signed impact
parameter dip of the V 0 with respect to the primary vertex.
This variable is defined as the distance of closest approach
of the V 0 trajectory to the primary vertex, and its sign is
that of the scalar product of the V 0 momentum and the
vector pointing from the primary vertex to the point of
closest approach. The distributions of the signed impact
parameter are shown in Fig. 2 together with the distributions of the corresponding pull, defined as dip divided by its
uncertainty dip calculated from the decay track parameter
uncertainties. The quality of the description of the data by
the simulation is good, including the tails at positive
impact-parameter values. The large pulls for secondary baryons from cascade decays allow the suppression of this
background by means of the kinematic fit.
The uncorrected average rates of reconstructed V 0 candidates passing the selection cuts per unit pseudorapidity
are shown in Fig. 3 as a function of the difference in
azimuthal angle jj between the V 0 candidate and the
leading charged-particle jet. Uncorrected data are compared to PYTHIA events passed through the detailed detector simulation. The dependence of the rates on jj is
qualitatively described by the PYTHIA tunes considered.
The simulation underestimates significantly the V 0 rates
in the transverse region. The peak at jj 0 is more
pronounced for baryons than for KS0 mesons. The simulation indicates that the harder pT cut applied to the baryon
candidates is responsible for this feature; the distributions
are similar when the same pT cut is applied to both V 0
types.
The backgrounds to the KS0 and samples are estimated
with two methods. The first is based on simulation.
Candidates not matched to a generated primary V 0 of the
corresponding type are counted as background. The
PYTHIA 6 D6T sample is used. To account for the known
deficit of strange particles in the simulation (see Sec. I), the
contribution from KS0 mesons misidentified as baryons is
weighted by the ratio of KS0 rates measured in nonsingle
diffractive events to those in PYTHIA 6 D6T, 1.39 [11].
Similarly, the contribution from misidentified baryons
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MEASUREMENT OF NEUTRAL STRANGE PARTICLE . . .
105
Data
0
Primary K
104
Misidentified V
PHYSICAL REVIEW D 88, 052001 (2013)
s = 7 TeV
CMS, pp,
Candidates / 0.05 cm
Candidates / 0.2 cm
CMS, pp,
K0S
S
0
Other sources
103
102
10
Data
104
Primary Λ
-5
103
Misidentified V
0
Other sources
102
10
0
5
-2
-1
dip [cm]
CMS, pp,
0
1
2
dip [cm]
s = 7 TeV
CMS, pp,
5
10
s = 7 TeV
104
K0S
Candidates
104
Candidates
Λ
Cascade decays
1
1
103
102
10
1
-40
s = 7 TeV
Λ
103
102
10
1
-20
0
20
40
-40
dip/ σd
-20
0
20
40
dip/ σd
ip
ip
FIG. 2 (color online). Distributions of the signed impact parameter dip with respect to the primary vertex, and the corresponding pull
distributions, for the most probable particle-type hypothesis determined by the kinematic fit. The black points indicate the data. The
histograms show the backgrounds (hatched: misidentified V 0 ; green: nonprimary from and cascade decays; grey: other sources)
and the signal (yellow) as predicted by PYTHIA 6 D6T. The PYTHIA prediction is normalized to the data.
is weighted by a factor of 1.85, and the contribution arising
from nonprimary baryons from and decays is
weighted by the ratio of the measured and simulated production rates, 2.67 [11].
The second method is based on data. The signal and
background contributions are extracted from a fit to the
distribution of the kinematic-fit 2 probability, with signal
and background shapes obtained from simulation. Apart
from the background normalization, the measured and
simulated pull distributions of the constrained variables
(Figs. 1 and 2), as well as the measured and simulated
2 -probability distributions (not shown), are in good
agreement. These facts, as well as goodness-of-fit tests,
validate the approach.
In both methods, the background is estimated as a
function of the charged-particle jet pT for the rate measurements, and as a function of the V 0 pT for the V 0 pT
spectra and the pT sum measurements. The background
estimations from the two methods are in reasonable agreement, and they exhibit the same dependence on the
charged-particle jet and V 0 pT . The final background estimates are computed as the average of the results of the two
methods, and the corresponding systematic uncertainties
are taken as half the difference of the two results. The
background fraction for KS0 increases from ð1:5 1:1Þ% at
charged-particle jet pT ¼ 1 GeV=c to ð3:3 1:7Þ% at
charged-particle jet pT ¼ 10 GeV=c and remains constant
at higher charged-particle jet pT . The background is
ð8 2Þ% for baryons, independent of the charged-particle
jet pT .
The KS0 and raw yields are corrected for purity
(defined as 1—background fraction) as well as for acceptance and reconstruction efficiency. Each V 0 candidate is
1
, where A
weighted by the product of the purity times A
denotes the acceptance of the cuts on the V 0 transverse
flight distance and on the pT , of the decay particles, and
denotes the reconstruction and selection efficiency for
accepted V 0 candidates. The product of acceptance times
efficiency is computed in V 0 ðpT ; Þ bins from a sample of
50 106 PYTHIA 6 D6T minimum-bias events passed
through the detailed detector simulation. The average values of the product of acceptance and efficiency in this
baryons within the
sample for KS0 mesons, and and kinematic cuts (jj < 2; pT > 600 MeV=c for KS0 , pT >
are 11.3%, 8.4%, and 6.6%,
1:5 GeV=c for and )
respectively, including the branching fractions BðK0S !
! p
þÞ ¼
þ Þ ¼ 69:2% and Bð ! p Þ ¼ Bð
63:9% [29]. The acceptance depends strongly on the V 0
052001-5
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PHYSICAL REVIEW D 88, 052001 (2013)
Λ
3
s
-1
3
10 / ∆ η × d⟨N ⟩/d(|∆ φ|) [deg-1] 10 / ∆ η × d⟨NK0⟩/d(|∆ φ|) [deg ]
CMS, pp,
0.3
Data
0.25
0.2
PYTHIA
6 Z1
PYTHIA
6 D6T
PYTHIA
8 Tune 1
s = 7 TeV
III. SYSTEMATIC UNCERTAINTIES
K0s
0.15
0.1
0.05
0.1
Λ
0.08
0.06
0.04
0.02
0
20
40
60
80 100 120 140 160 180
|∆φ| [deg]
FIG. 3 (color online). Uncorrected average rate of selected
V 0 candidates per event, per degree, and per unit pseudorapidity within jj < 2, as a function of the difference in azimuthal
angle jj between the V 0 candidate and the leading chargedparticle jet. Data and detailed simulation of minimum-bias
events with different PYTHIA tunes are shown for reconstructed charged-particle jet pT > 1 GeV=c. Top: KS0 candidates
with pT > 600 MeV=c; bottom: candidates with pT >
1:5 GeV=c.
pT , while the efficiency varies by a factor of about 2 in
the V 0 pT and ranges selected. The smaller efficiency
baryons than for baryons reflects the higher
for interaction cross section of antiprotons with the detector
material compared to that of protons. The corrected and
yields are found to be compatible when accounting for
the systematic uncertainty due to the modeling of the
antiproton cross section in the GEANT4 version used [30]
(see Sec. III).
The consistency of the correction method was checked
by applying it to all other Monte Carlo samples and comparing the results to the known generated values. Further
support to the correction procedure is provided by the fact
that the simulation reproduces well several key aspects of
the data, most notably the reconstruction efficiency [23,24]
and the angular distributions of the V 0 decay tracks as a
function of the V 0 pT . The reliability of the simulation for
KS0 and reconstruction was checked by comparing the
lifetimes obtained from fits to the corrected proper time
distributions with the world averages [11]. The stability of
the results when varying the V 0 selection cuts was also
checked. The resulting overall contribution of the V 0
reconstruction to the systematic uncertainty is given in
Sec. III.
The main sources of systematic uncertainties are described
below, with numerical values summarized in Table I.
Leading charged-particle jet selection: The bias in rates
and pT sums due to mismatches between the reconstructed
and the simulated leading charged-particle jets is corrected
by means of detailed simulations. The systematic uncertainty is estimated from the residual difference in rates and
pT sums when the reconstructed and the simulated leading
charged-particle jets are matched within R ¼ 0:3.
Primary vertex selection: The bias caused by the requirement of a minimum track multiplicity at the primary vertex
is corrected by means of detailed simulations of minimumbias events with the PYTHIA 6 Z1 tune. The primary
charged-particle multiplicity in 7 TeV pp collisions is
well described by this tune [1]. The corresponding uncertainty is estimated from the spread of the corrections computed with PYTHIA 6 tunes D6T, Z1 and PYTHIA 8 tune 1.
Modeling of V 0 reconstruction efficiency: The systematic
uncertainty on the V 0 reconstruction efficiency is estimated
from closure tests and from the stability of the results with
respect to the V 0 selection cuts, as described in Sec. II B.
TABLE I. Systematic uncertainties on the measured average
V 0 rates and pT sums.
Average rates
Source
Leading charged-particle jet selection
Primary vertex selection
Modeling of V 0 efficiency
Charged-particle jet pT 2:5 GeV=c
Charged-particle jet pT > 2:5 GeV=c
Detector material
GEANT4 cross sections
Statistical uncertainty on V 0 weights
0
600 MeV=c < pVT < 700 MeV=c
0
1:5 GeV=c < pVT < 1:6 GeV=c
0
6 GeV=c < pVT < 8 GeV=c
Background estimation
Charged-particle jet pT ¼ 1 GeV=c
Charged-particle jet pT ¼ 10 GeV=c
KS0 (%)
(%)
3
1
7
1
3
3
3
10
3
3
5
0.1
0.03
1.4
0.33
8.3
1.1
1.7
2
2
6
6
14
10
KS0 (%)
(%)
0.1
0.8
3.6
0.3
4.0
as rates
as rates
Total
Charged-particle jet pT ¼ 1 GeV=c
Charged-particle jet pT ¼ 10 GeV=c
Average pT sums
Source
Background estimation
0
pVT ¼ 600 MeV=c
0
pVT ¼ 1:5 GeV=c
0
pVT ¼ 8 GeV=c
Other sources
052001-6
MEASUREMENT OF NEUTRAL STRANGE PARTICLE . . .
PHYSICAL REVIEW D 88, 052001 (2013)
×10-3
140
Detector material: The overall mass of the tracker and
the relative fractions of the different tracker materials are
varied in the simulations, with the requirement that the
resulting predicted tracker weight be consistent with the
measured weight [31]. The difference between the results
thus obtained and the nominal results is taken as a contribution to the systematic uncertainty.
GEANT4 cross sections: A 5% systematic uncertainty is
assigned to the baryon yields, as a result of the known
imperfect modeling of the low-energy antiproton interaction cross section in the GEANT4 version used [30].
Statistical uncertainty on the V 0 yield correction: A
small contribution to the total uncertainty stems from the
finite size of the sample of minimum-bias events passed
through the full detector simulation (50 106 events),
from which the correction is computed.
Estimation of V 0 background: The uncertainty on the
background remaining after V 0 identification by means of
the kinematic fit is taken as half the difference between the
results of the two background estimation methods used.
The uncertainty on the beam spot position and size gives
a negligible contribution to the total uncertainty.
CMS, pp,
s = 7 TeV
Data
6 Z2*
6 Z1
PYTHIA 6 D6T
PYTHIA 8 Tune 1
PYTHIA
120
PYTHIA
Ks
⟨N 0⟩/ ∆η ∆ |∆φ|
100
80
60
40
Primary K0
20
S
o
o
60 < |∆ φ| < 120 , pT > 0.6 GeV/c
0
10
20
Syst. uncertainty
MC
0
Ks
Ks
⟨N 0 ⟩/ ⟨N
Data
⟩
1.4
30
40
50
30
40
50
Total uncertainty
1.2
1
0.8
0.6
0
10
20
leading charged-particle jet p [GeV/c]
T
×10-3
IV. RESULTS
45
The V production rates in the transverse region are
shown in Fig. 4 as a function of the leading chargedparticle jet pT , and the V 0 scalar pT sums in the transverse
region are shown in Fig. 5.
The rates and pT sums exhibit a rise with increasing hard
scale, followed by a plateau. The turn-on of the plateau is
located at charged-particle jet pT ’ 10 GeV=c for both
primary mesons and baryons. Above the turn-on, the rates
and pT sums are essentially constant, implying also a
constant strange-particle average pT above the turn-on.
A comparison can be made with the trends observed for
charged primary particles [1] in spite of the different jet
reconstruction algorithm used in Ref. [1] (SISCone). The
dependence of the UE activity on the charged-particle jet
pT is very similar to that observed for charged primary
particles [1,3,4]. The most striking feature is that the pT
scale at whichpffiffithe
ffi plateau starts, around 10 GeV=c in pp
collisions at s ¼ 7 TeV, is independent of the type of
primary particle used to probe the UE activity. These
observations are consistent with the impact-parameter picture of particle production in hadron collisions [6,7], in
which the MPI contribution saturates at scales typical of
central collisions.
The PYTHIA 6 Z1 and Z2 tunes qualitatively reproduce
the dependence of the KS0 rate and pT sum on the chargedparticle jet pT , but exhibit a 10%–15% deficit in the yield,
independent of the charged-particle jet pT . PYTHIA 8 tune 1
underestimates the activity by about 30%. For the baryons, PYTHIA 6 tunes Z1, Z2 and PYTHIA 8 tune 1 underestimate the rates by about 50%. After being tuned to the
charged-particle data, PYTHIA 6 Z2 models strangeness
40
0
CMS, pp,
s = 7 TeV
Data
6 Z2*
6 Z1
PYTHIA 6 D6T
PYTHIA 8 Tune 1
PYTHIA
PYTHIA
⟨NΛ⟩/ ∆η ∆ |∆φ|
35
30
25
20
15
10
Primary Λ
60o < |∆ φ| < 120o, pT > 1.5 GeV/c
Syst. uncertainty
1.5
Total uncertainty
1
MC
⟨NΛ ⟩/ ⟨NΛ
Data
⟩
5
0.5
0
10
20
30
40
50
leading charged-particle jet p [GeV/c]
T
FIG. 4 (color online). Average multiplicity per unit of pseudorapidity and per radian in the transverse region (jj < 2,
60 < jj < 120 ), as a function of the pT of the leading
charged-particle jet: (top) KS0 with pT > 0:6 GeV=c; (bottom)
with pT > 1:5 GeV=c. Predictions of PYTHIA tunes are
compared to the data, and the ratios of simulations to data are
shown in the bottom panels. For the data, the statistical uncertainties (error bars) and the quadratic sum of statistical and
systematic uncertainties (error band) are shown, while for simulations the uncertainty is only shown for PYTHIA 6 tune Z2 , for
clarity.
052001-7
S. CHATRCHYAN et al.
PHYSICAL REVIEW D 88, 052001 (2013)
CMS, pp,
0.18
6 Z2*
6 Z1
PYTHIA 6 D6T
PYTHIA 8 Tune 1
PYTHIA
PYTHIA
0.14
0.12
0.1
0.08
T
K0
production in the UE in a very similar way as Z1, in spite of
the different parton distribution set used.
PYTHIA 6 D6T shows a dependence of the activity on the
charged-particle jet pT that differs from that of the data and
of the other tunes. In addition, the V 0 pT distributions
predicted by PYTHIA 6 D6T in the transverse region are
in strong disagreement with the data. As an illustration,
the pT spectra are shown in Fig. 6 for events with a
Data
0.16
⟨Σ p s⟩/ ∆η ∆ |∆φ| [GeV/c]
s = 7 TeV
0.06
CMS, pp,
0.04
s = 7 TeV
Primary K0
S
0.02
Data
60o < |∆ φ| < 120o, pT > 0.6 GeV/c
6
Candidates / GeV/c
⟩
0
T,Ks
Data
⟩/ ⟨Σ p
10
10
20
30
40
50
leading
charged-particle jet pT [GeV/c]
Syst.
uncertainty
Total uncertainty
1.2
T,Ks
0
1
0.8
⟨Σ p
MC
0
1.4
0.6
0
10
20
30
40
50
leading charged-particle jet p [GeV/c]
T
CMS, pp,
0.14
PYTHIA
6 D6T (x1.54)
PYTHIA
8 Tune 1 (x1.33)
104
s = 7 TeV
Primary K0
S
> 3 GeV/c
pjet
T
6 Z2*
6 Z1
PYTHIA 6 D6T
PYTHIA 8 Tune 1
PYTHIA
0.12
103
PYTHIA
0.1
60o < |∆φ| < 120o
0
2
4
6
8
K0s pT [GeV/c]
0.08
CMS, pp,
s = 7 TeV
0.06
106
T
⟨Σ pΛ⟩/ ∆η ∆ |∆φ| [GeV/c]
6 Z1 (x0.98)
105
Data
Data
Candidates / GeV/c
0.04
Primary Λ
0.02
o
o
60 < |∆ φ| < 120 , pT > 1.5 GeV/c
1.5
0
T,Λ
⟨Σ pMC⟩/ ⟨Σ pData⟩
PYTHIA
10
20
30
Syst. uncertainty
40
50
uncertainty
leadingTotal
charged-particle
jet p [GeV/c]
T
T,Λ
1
5
10
PYTHIA
6 Z1 (x1.88)
PYTHIA
6 D6T (x1.97)
PYTHIA
8 Tune 1 (x2.32)
104
Primary Λ
0.5
0
10
20
30
40
pjet > 3 GeV/c
50
T
3
10
leading charged-particle jet p [GeV/c]
T
FIG. 5 (color online). Average scalar pT sum per unit of
pseudorapidity and per radian in the transverse region (jj < 2,
60 < jj < 120 ), as a function of the pT of the leading
charged-particle jet: (top) KS0 with pT > 0:6 GeV=c; (bottom)
with pT > 1:5 GeV=c. Predictions of PYTHIA tunes are
compared to the data, and the ratios of simulations to data are
shown in the bottom panels. For the data, the statistical uncertainties (error bars) and the quadratic sum of statistical and
systematic uncertainties (error band) are shown, while for
simulations the uncertainty is only shown for PYTHIA 6 tune
Z2 , for clarity.
0
60o < |∆φ| < 120o
2
4
6
8
Λ pT [GeV/c]
FIG. 6 (color online). V 0 pT distributions corrected for selection efficiency and background without a correction to the
leading charged-particle jet, in the region transverse to a leading
reconstructed charged-particle jet with pT > 3 GeV=c, compared to predictions from different PYTHIA tunes (top: KS0 ;
bottom: ). Error bars indicate the quadratic sum of the statistical and systematic uncertainties. Simulations are normalized to
the first pT bin in the data, with normalization factors given in
parentheses.
052001-8
MEASUREMENT OF NEUTRAL STRANGE PARTICLE . . .
PHYSICAL REVIEW D 88, 052001 (2013)
CMS, pp, s = 7 TeV
0.14
CMS, pp, s = 7 TeV
0.16
Data
6 Z2*
PYTHIA 6 Z1
PYTHIA 6 D6T
PYTHIA 8 Tune 1
PYTHIA
⟩
T
charged
0.1
6 Z2*
6 Z1
PYTHIA 6 D6T
PYTHIA 8 Tune 1
PYTHIA
PYTHIA
⟨Σ p s⟩ / ⟨Σ p
0.12
0.1
0.08
0.06
T
0
0.08
K
Ks
⟨N 0⟩ / ⟨Ncharged⟩
0.12
Data
0.14
0.04
0.04
o
o
60 < |∆φ| < 120
0.02
0
KS
charged
pT > 0.6 GeV/c, pT
0
10
20
30
50
0
10
20
30
> 0.5 GeV/c
40
50
leading charged-particle jet pT [GeV/c]
CMS, pp, s = 7 TeV
CMS, pp, s = 7 TeV
40
0.1
Data
Data
6 Z2*
PYTHIA 6 Z1
PYTHIA 6 D6T
PYTHIA 8 Tune 1
PYTHIA
6 Z2*
6 Z1
PYTHIA 6 D6T
PYTHIA 8 Tune 1
PYTHIA
PYTHIA
⟩
0.08
charged
30
⟨Σ p Λ ⟩ / ⟨Σ p
25
T
35
20
T
⟨NΛ⟩ / ⟨Ncharged⟩
charged
pT > 0.6 GeV/c, pT
leading charged-particle jet pT [GeV/c]
×10-3
o
o
60 < |∆φ| < 120
0
KS
0.02
> 0.5 GeV/c
40
0.06
15
0.06
0.04
10
0.02
o
60o < |∆φ| < 120
5
charged
pΛT > 1.5 GeV/c, pT
0
10
20
30
o
60o < |∆φ| < 120
charged
pΛT > 1.5 GeV/c, pT
> 0.5 GeV/c
40
50
0
10
20
30
> 0.5 GeV/c
40
50
leading charged-particle jet pT [GeV/c]
leading charged-particle jet pT [GeV/c]
FIG. 7 (color online). Ratios of the average multiplicities and scalar pT sums for primary V 0 in the transverse region to the same
quantities for primary charged particles [1] as a function of charged-particle jet pT . The error bars indicate the quadratic sum of the
statistical and systematic uncertainties.
reconstructed charged-particle jet pT > 3 GeV=c (without
a correction to the leading charged hadron jet). For the KS0
case, in the pT range observed (pT > 600 MeV=c), PYTHIA
6 tune D6T shows a much harder spectrum than the data,
while tune Z1 shows a softer spectrum and PYTHIA 8 tune 1
reproduces the shape well. For the case, in the pT >
1:5 GeV=c range, PYTHIA 6 D6T shows a much harder
spectrum than the data, while the other simulations
describe the data reasonably well.
The ratios of the rates and pT sums of primary V 0
mesons to the rates and pT sums of primary charged
particles from Ref. [1] are shown in Fig. 7. The data are
integrated over the same pseudorapidity range for strange
and charged particles, jj < 2. The KS0 to charged-particle
activity ratios are constant in the charged-particle jet pT
range 3–50 GeV=c, i.e. almost throughout the whole range
studied and, specifically, across the turn-on of the plateau
around 10 GeV=c. An increase is seen below 3 GeV=c.
This feature is also present in the simulations but is not as
pronounced as in the data, and not in all tunes studied.
The to charged-particle activity ratios exhibit a rise
for charged-particle jet pT < 10 GeV=c, followed by a
plateau. A similar dependence is visible in PYTHIA.
Simulations indicate that the rise is related to the observed
hardening of the baryon pT spectrum as the chargedparticle jet pT increases, combined with the 1:5 GeV=c
pT cut applied to the baryon sample. When the baryon pT
cut is decreased to 0:5 GeV=c as for charged particles,
constant ratios are predicted.
Constant strange- to charged-particle activity ratios have
thus been measured for KS0 mesons for charged-particle jet
pT > 3 GeV=c and for baryons for charged-particle jet
pT > 10 GeV=c. In addition, as just discussed, when
accounting for the acceptance of the baryon pT cut, a
052001-9
S. CHATRCHYAN et al.
PHYSICAL REVIEW D 88, 052001 (2013)
constant ratio is also predicted for baryons at chargedparticle jet pT < 10 GeV=c. Since the trends observed are
very similar for charged and strange particles, as well as for
mesons and baryons, the present measurements suggest
that hadronization and MPI are decoupled.
V. CONCLUSIONS
This paper describes measurements
pffiffiffi of the underlying
event activity in pp collisions at s ¼ 7 TeV, probed
through the production of primary KS0 mesons and baryons. The production of KS0 mesons and baryons in
K0
the kinematic range pT S > 0:6 GeV=c, p
T > 1:5 GeV=c
and jj < 2 is analyzed in the transverse region, defined
as 60 < jj < 120 , with the difference in azimuthal angle between the leading charged-particle jet and
the strange-particle directions. The average multiplicity
and the average scalar pT sum of primary particles per
event are studied as a function of the leading chargedparticle jet pT .
A steep rise of the underlying event activity is seen with
increasing leading jet pT , followed by a ‘‘saturation’’
region for jet pT > 10 GeV=c. This trend and the pT scale
above which saturation occurs are very similar to those
observed with charged primary particles. The similarity of
the behavior for strange and charged particles is consistent
with the impact-parameter picture of multiple parton interactions in pp collisions, in which the centrality of the pp
collision and the MPI activity are correlated.
The results are compared to recent tunes of the PYTHIA
Monte Carlo event generator. The PYTHIA simulations
underestimate the data by 15%–30% for KS0 mesons and
by about 50% for baryons, a MC deficit similar to that
observed for the inclusive strange-particle production in
pp collisions.
The constant strange- to charged-particle activity ratios
and the similar trends for mesons and baryons indicate that
the MPI dynamics is decoupled from parton hadronization,
with the latter occurring at a later stage.
ACKNOWLEDGMENTS
We congratulate our colleagues in the CERN accelerator
departments for the excellent performance of the LHC and
thank the technical and administrative staffs at CERN and
at other CMS institutes for their contributions to the
success of the CMS effort. In addition, we gratefully
acknowledge the computing centers and personnel of the
Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the
construction and operation of the LHC and the CMS
detector provided by the following funding agencies:
the Austrian Federal Ministry of Science and Research
and the Austrian Science Fund; the Belgian Fonds de la
Recherche Scientifique, and Fonds voor Wetenschappelijk
Onderzoek; the Brazilian Funding Agencies (CNPq,
CAPES, FAPERJ, and FAPESP); the Bulgarian Ministry
of Education, Youth and Science; CERN; the Chinese
Academy of Sciences, Ministry of Science and
Technology, and National Natural Science Foundation of
China; the Colombian Funding Agency (COLCIENCIAS);
the Croatian Ministry of Science, Education and Sport; the
Research Promotion Foundation, Cyprus; the Ministry of
Education and Research, Recurrent financing Contract
No. SF0690030s09 and European Regional Development
Fund, Estonia; the Academy of Finland, Finnish Ministry of
Education and Culture, and Helsinki Institute of Physics;
the Institut National de Physique Nucléaire et de Physique
des Particules/CNRS, and Commissariat à l’Énergie
Atomique et aux Énergies Alternatives/CEA, France; the
Bundesministerium für Bildung und Forschung, Deutsche
Forschungsgemeinschaft, and Helmholtz-Gemeinschaft
Deutscher Forschungszentren, Germany; the General
Secretariat for Research and Technology, Greece; the
National Scientific Research Foundation, and National
Office for Research and Technology, Hungary; the
Department of Atomic Energy and the Department of
Science and Technology, India; the Institute for Studies in
Theoretical Physics and Mathematics, Iran; the Science
Foundation, Ireland; the Istituto Nazionale di Fisica
Nucleare, Italy; the Korean Ministry of Education,
Science and Technology and the World Class University
program of NRF, Republic of Korea; the Lithuanian
Academy of Sciences; the Mexican Funding Agencies
(CINVESTAV, CONACYT, SEP, and UASLP-FAI); the
Ministry of Science and Innovation, New Zealand; the
Pakistan Atomic Energy Commission; the Ministry of
Science and Higher Education and the National Science
Centre, Poland; the Fundação para a Ciência e a Tecnologia,
Portugal; JINR (Armenia, Belarus, Georgia, Ukraine,
Uzbekistan); the Ministry of Education and Science of the
Russian Federation, the Federal Agency of Atomic Energy
of the Russian Federation, Russian Academy of Sciences,
and the Russian Foundation for Basic Research; the Ministry
of Science and Technological Development of Serbia; the
Secretarı́a de Estado de Investigación, Desarrollo e
Innovación and Programa Consolider-Ingenio 2010, Spain;
the Swiss Funding Agencies (ETH Board, ETH Zurich, PSI,
SNF, UniZH, Canton Zurich, and SER); the National
Science Council, Taipei; the Thailand Center of
Excellence in Physics, the Institute for the Promotion of
Teaching Science and Technology of Thailand and the
National Science and Technology Development Agency of
Thailand; the Scientific and Technical Research Council of
Turkey, and Turkish Atomic Energy Authority; the Science
and Technology Facilities Council, UK; and the US
Department of Energy and National Science Foundation.
Individuals have received support from the Marie-Curie
programme and the European Research Council and
EPLANET (European Union); the Leventis Foundation;
052001-10
MEASUREMENT OF NEUTRAL STRANGE PARTICLE . . .
PHYSICAL REVIEW D 88, 052001 (2013)
the A. P. Sloan Foundation; the Alexander von Humboldt
Foundation; the Belgian Federal Science Policy Office; the
Fonds pour la Formation à la Recherche dans l’Industrie et
dans l’Agriculture (FRIA-Belgium); the Agentschap voor
Innovatie door Wetenschap en Technologie (IWT-Belgium);
the Ministry of Education, Youth and Sports (MEYS) of
Czech Republic; the Council of Science and Industrial
Research, India; the Compagnia di San Paolo (Torino); the
HOMING PLUS programme of Foundation for Polish
Science, cofinanced by EU, Regional Development Fund;
and the Thalis and Aristeia programmes cofinanced by
EU-ESF and the Greek NSRF.
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J. Duarte Campderros,97 M. Fernandez,97 G. Gomez,97 J. Gonzalez Sanchez,97 A. Graziano,97 C. Jorda,97
A. Lopez Virto,97 J. Marco,97 R. Marco,97 C. Martinez Rivero,97 F. Matorras,97 F. J. Munoz Sanchez,97 T. Rodrigo,97
A. Y. Rodrı́guez-Marrero,97 A. Ruiz-Jimeno,97 L. Scodellaro,97 I. Vila,97 R. Vilar Cortabitarte,97 D. Abbaneo,98
E. Auffray,98 G. Auzinger,98 M. Bachtis,98 P. Baillon,98 A. H. Ball,98 D. Barney,98 J. Bendavid,98 J. F. Benitez,98
C. Bernet,98,i G. Bianchi,98 P. Bloch,98 A. Bocci,98 A. Bonato,98 O. Bondu,98 C. Botta,98 H. Breuker,98
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A. Dabrowski,98 A. De Roeck,98 S. De Visscher,98 S. Di Guida,98 M. Dobson,98 N. Dupont-Sagorin,98
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J. R. Vlimant,98 H. K. Wöhri,98 S. D. Worm,98,kk W. D. Zeuner,98 W. Bertl,99 K. Deiters,99 W. Erdmann,99
K. Gabathuler,99 R. Horisberger,99 Q. Ingram,99 H. C. Kaestli,99 S. König,99 D. Kotlinski,99 U. Langenegger,99
D. Renker,99 T. Rohe,99 F. Bachmair,100 L. Bäni,100 P. Bortignon,100 M. A. Buchmann,100 B. Casal,100 N. Chanon,100
A. Deisher,100 G. Dissertori,100 M. Dittmar,100 M. Donegà,100 M. Dünser,100 P. Eller,100 K. Freudenreich,100
C. Grab,100 D. Hits,100 P. Lecomte,100 W. Lustermann,100 A. C. Marini,100 P. Martinez Ruiz del Arbol,100 N. Mohr,100
F. Moortgat,100 C. Nägeli,100,ll P. Nef,100 F. Nessi-Tedaldi,100 F. Pandolfi,100 L. Pape,100 F. Pauss,100 M. Peruzzi,100
F. J. Ronga,100 M. Rossini,100 L. Sala,100 A. K. Sanchez,100 A. Starodumov,100,mm B. Stieger,100 M. Takahashi,100
L. Tauscher,100,a A. Thea,100 K. Theofilatos,100 D. Treille,100 C. Urscheler,100 R. Wallny,100 H. A. Weber,100
C. Amsler,101,nn V. Chiochia,101 C. Favaro,101 M. Ivova Rikova,101 B. Kilminster,101 B. Millan Mejias,101
P. Otiougova,101 P. Robmann,101 H. Snoek,101 S. Taroni,101 S. Tupputi,101 M. Verzetti,101 M. Cardaci,102
K. H. Chen,102 C. Ferro,102 C. M. Kuo,102 S. W. Li,102 W. Lin,102 Y. J. Lu,102 R. Volpe,102 S. S. Yu,102 P. Bartalini,103
P. Chang,103 Y. H. Chang,103 Y. W. Chang,103 Y. Chao,103 K. F. Chen,103 C. Dietz,103 U. Grundler,103 W.-S. Hou,103
Y. Hsiung,103 K. Y. Kao,103 Y. J. Lei,103 R.-S. Lu,103 D. Majumder,103 E. Petrakou,103 X. Shi,103 J. G. Shiu,103
Y. M. Tzeng,103 M. Wang,103 B. Asavapibhop,104 N. Suwonjandee,104 A. Adiguzel,105 M. N. Bakirci,105,oo
S. Cerci,105,pp C. Dozen,105 I. Dumanoglu,105 E. Eskut,105 S. Girgis,105 G. Gokbulut,105 E. Gurpinar,105 I. Hos,105
E. E. Kangal,105 A. Kayis Topaksu,105 G. Onengut,105,qq K. Ozdemir,105 S. Ozturk,105,oo A. Polatoz,105 K. Sogut,105,rr
D. Sunar Cerci,105,pp B. Tali,105,pp H. Topakli,105,oo M. Vergili,105 I. V. Akin,106 T. Aliev,106 B. Bilin,106 S. Bilmis,106
M. Deniz,106 H. Gamsizkan,106 A. M. Guler,106 G. Karapinar,106,ss K. Ocalan,106 A. Ozpineci,106 M. Serin,106
R. Sever,106 U. E. Surat,106 M. Yalvac,106 M. Zeyrek,106 E. Gülmez,107 B. Isildak,107,tt M. Kaya,107,uu O. Kaya,107,uu
S. Ozkorucuklu,107,vv N. Sonmez,107,ww H. Bahtiyar,108,xx E. Barlas,108 K. Cankocak,108 Y. O. Günaydin,108,yy
F. I. Vardarl,108 M. Yücel,108 L. Levchuk,109 P. Sorokin,109 J. J. Brooke,110 E. Clement,110 D. Cussans,110
H. Flacher,110 R. Frazier,110 J. Goldstein,110 M. Grimes,110 G. P. Heath,110 H. F. Heath,110 L. Kreczko,110
S. Metson,110 D. M. Newbold,110,kk K. Nirunpong,110 A. Poll,110 S. Senkin,110 V. J. Smith,110 T. Williams,110
L. Basso,111,zz K. W. Bell,111 A. Belyaev,111,zz C. Brew,111 R. M. Brown,111 D. J. A. Cockerill,111 J. A. Coughlan,111
K. Harder,111 S. Harper,111 J. Jackson,111 E. Olaiya,111 D. Petyt,111 B. C. Radburn-Smith,111
C. H. Shepherd-Themistocleous,111 I. R. Tomalin,111 W. J. Womersley,111 R. Bainbridge,112 O. Buchmuller,112
D. Burton,112 D. Colling,112 N. Cripps,112 M. Cutajar,112 P. Dauncey,112 G. Davies,112 M. Della Negra,112
W. Ferguson,112 J. Fulcher,112 D. Futyan,112 A. Gilbert,112 A. Guneratne Bryer,112 G. Hall,112 Z. Hatherell,112
J. Hays,112 G. Iles,112 M. Jarvis,112 G. Karapostoli,112 M. Kenzie,112 R. Lane,112 R. Lucas,112,kk L. Lyons,112
A.-M. Magnan,112 J. Marrouche,112 B. Mathias,112 R. Nandi,112 J. Nash,112 A. Nikitenko,112,mm J. Pela,112
M. Pesaresi,112 K. Petridis,112 M. Pioppi,112,aaa D. M. Raymond,112 S. Rogerson,112 A. Rose,112 C. Seez,112
P. Sharp,112,a A. Sparrow,112 A. Tapper,112 M. Vazquez Acosta,112 T. Virdee,112 S. Wakefield,112 N. Wardle,112
T. Whyntie,112 M. Chadwick,113 J. E. Cole,113 P. R. Hobson,113 A. Khan,113 P. Kyberd,113 D. Leggat,113 D. Leslie,113
W. Martin,113 I. D. Reid,113 P. Symonds,113 L. Teodorescu,113 M. Turner,113 J. Dittmann,114 K. Hatakeyama,114
A. Kasmi,114 H. Liu,114 T. Scarborough,114 O. Charaf,115 S. I. Cooper,115 C. Henderson,115 P. Rumerio,115
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J. St. John,116 L. Sulak,116 J. Alimena,117 S. Bhattacharya,117 G. Christopher,117 D. Cutts,117 Z. Demiragli,117
A. Ferapontov,117 A. Garabedian,117 U. Heintz,117 G. Kukartsev,117 E. Laird,117 G. Landsberg,117 M. Luk,117
M. Narain,117 M. Segala,117 T. Sinthuprasith,117 T. Speer,117 R. Breedon,118 G. Breto,118
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C. Silkworth,133 D. Strom,133 P. Turner,133 N. Varelas,133 U. Akgun,134 E. A. Albayrak,134,xx B. Bilki,134,fff
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(CMS Collaboration)
1
Yerevan Physics Institute, Yerevan, Armenia
Institut für Hochenergiephysik der OeAW, Wien, Austria
3
National Centre for Particle and High Energy Physics, Minsk, Belarus
4
Universiteit Antwerpen, Antwerpen, Belgium
5
Vrije Universiteit Brussel, Brussel, Belgium
6
Université Libre de Bruxelles, Bruxelles, Belgium
7
Ghent University, Ghent, Belgium
8
Université Catholique de Louvain, Louvain-la-Neuve, Belgium
9
Université de Mons, Mons, Belgium
10
Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
11
Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
12a
Universidade Estadual Paulista, São Paulo, Brazil
12b
Universidade Federal do ABC, São Paulo, Brazil
13
Institute for Nuclear Research and Nuclear Energy, Sofia, Bulgaria
14
University of Sofia, Sofia, Bulgaria
15
Institute of High Energy Physics, Beijing, China
2
052001-17
S. CHATRCHYAN et al.
PHYSICAL REVIEW D 88, 052001 (2013)
16
State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China
17
Universidad de Los Andes, Bogota, Colombia
18
Technical University of Split, Split, Croatia
19
University of Split, Split, Croatia
20
Institute Rudjer Boskovic, Zagreb, Croatia
21
University of Cyprus, Nicosia, Cyprus
22
Charles University, Prague, Czech Republic
23
Academy of Scientific Research and Technology of the Arab Republic of Egypt,
Egyptian Network of High Energy Physics, Cairo, Egypt
24
National Institute of Chemical Physics and Biophysics, Tallinn, Estonia
25
Department of Physics, University of Helsinki, Helsinki, Finland
26
Helsinki Institute of Physics, Helsinki, Finland
27
Lappeenranta University of Technology, Lappeenranta, Finland
28
DSM/IRFU, CEA/Saclay, Gif-sur-Yvette, France
29
Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France
30
Institut Pluridisciplinaire Hubert Curien, Université de Strasbourg, Université de Haute Alsace Mulhouse,
CNRS/IN2P3, Strasbourg, France
31
Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France
32
Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucléaire de Lyon, Villeurbanne, France
33
Institute of High Energy Physics and Informatization, Tbilisi State University, Tbilisi, Georgia
34
RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany
35
RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany
36
RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany
37
Deutsches Elektronen-Synchrotron, Hamburg, Germany
38
University of Hamburg, Hamburg, Germany
39
Institut für Experimentelle Kernphysik, Karlsruhe, Germany
40
Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
41
University of Athens, Athens, Greece
42
University of Ioánnina, Ioánnina, Greece
43
KFKI Research Institute for Particle and Nuclear Physics, Budapest, Hungary
44
Institute of Nuclear Research ATOMKI, Debrecen, Hungary
45
University of Debrecen, Debrecen, Hungary
46
Panjab University, Chandigarh, India
47
University of Delhi, Delhi, India
48
Saha Institute of Nuclear Physics, Kolkata, India
49
Bhabha Atomic Research Centre, Mumbai, India
50
Tata Institute of Fundamental Research-EHEP, Mumbai, India
51
Tata Institute of Fundamental Research-HECR, Mumbai, India
52
Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
53
University College Dublin, Dublin, Ireland
54a
INFN Sezione di Bari, Bari, Italy
54b
Università di Bari, Bari, Italy
54c
Politecnico di Bari, Bari, Italy
55a
INFN Sezione di Bologna, Bologna, Italy
55b
Università di Bologna, Bologna, Italy
56a
INFN Sezione di Catania, Catania, Italy
56b
Università di Catania, Catania, Italy
57a
INFN Sezione di Firenze, Firenze, Italy
57b
Università di Firenze, Firenze, Italy
58
INFN Laboratori Nazionali di Frascati, Frascati, Italy
59a
INFN Sezione di Genova, Genova, Italy
59b
Università di Genova, Genova, Italy
60a
INFN Sezione di Milano-Bicocca, Milano, Italy
60b
Università di Milano-Bicocca, Milano, Italy
61a
INFN Sezione di Napoli, Napoli, Italy
61b
Università di Napoli ‘Federico II’, Napoli, Italy
61c
Università della Basilicata (Potenza), Napoli, Italy
61d
Università G. Marconi (Roma), Napoli, Italy
62a
INFN Sezione di Padova, Padova, Italy
62b
Università di Padova, Padova, Italy
62c
Università di Trento (Trento), Padova, Italy
052001-18
MEASUREMENT OF NEUTRAL STRANGE PARTICLE . . .
63a
PHYSICAL REVIEW D 88, 052001 (2013)
INFN Sezione di Pavia, Pavia, Italy
Università di Pavia, Pavia, Italy
64a
INFN Sezione di Perugia, Perugia, Italy
64b
Università di Perugia, Perugia, Italy
65a
INFN Sezione di Pisa, Pisa, Italy
65b
Università di Pisa, Pisa, Italy
65c
Scuola Normale Superiore di Pisa, Pisa, Italy
66a
INFN Sezione di Roma, Roma, Italy
66b
Università di Roma, Roma, Italy
67a
INFN Sezione di Torino, Torino, Italy
67b
Università di Torino, Torino, Italy
67c
Università del Piemonte Orientale (Novara), Torino, Italy
68a
INFN Sezione di Trieste, Trieste, Italy
68b
Università di Trieste, Trieste, Italy
69
Kangwon National University, Chunchon, Korea
70
Kyungpook National University, Daegu, Korea
71
Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea
72
Korea University, Seoul, Korea
73
University of Seoul, Seoul, Korea
74
Sungkyunkwan University, Suwon, Korea
75
Vilnius University, Vilnius, Lithuania
76
Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico
77
Universidad Iberoamericana, Mexico City, Mexico
78
Benemerita Universidad Autonoma de Puebla, Puebla, Mexico
79
Universidad Autónoma de San Luis Potosı́, San Luis Potosı́, Mexico
80
University of Auckland, Auckland, New Zealand
81
University of Canterbury, Christchurch, New Zealand
82
National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan
83
National Centre for Nuclear Research, Swierk, Poland
84
Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland
85
Laboratório de Instrumentação e Fı́sica Experimental de Partı́culas, Lisboa, Portugal
86
Joint Institute for Nuclear Research, Dubna, Russia
87
Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia
88
Institute for Nuclear Research, Moscow, Russia
89
Institute for Theoretical and Experimental Physics, Moscow, Russia
90
P.N. Lebedev Physical Institute, Moscow, Russia
91
Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia
92
State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia
93
University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia
94
Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain
95
Universidad Autónoma de Madrid, Madrid, Spain
96
Universidad de Oviedo, Oviedo, Spain
97
Instituto de Fı́sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain
98
CERN, European Organization for Nuclear Research, Geneva, Switzerland
99
Paul Scherrer Institut, Villigen, Switzerland
100
Institute for Particle Physics, ETH Zurich, Zurich, Switzerland
101
Universität Zürich, Zurich, Switzerland
102
National Central University, Chung-Li, Taiwan
103
National Taiwan University (NTU), Taipei, Taiwan
104
Chulalongkorn University, Bangkok, Thailand
105
Cukurova University, Adana, Turkey
106
Middle East Technical University, Physics Department, Ankara, Turkey
107
Bogazici University, Istanbul, Turkey
108
Istanbul Technical University, Istanbul, Turkey
109
National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine
110
University of Bristol, Bristol, United Kingdom
111
Rutherford Appleton Laboratory, Didcot, United Kingdom
112
Imperial College, London, United Kingdom
113
Brunel University, Uxbridge, United Kingdom
114
Baylor University, Waco, Texas, USA
115
The University of Alabama, Tuscaloosa, Alabama, USA
63b
052001-19
S. CHATRCHYAN et al.
PHYSICAL REVIEW D 88, 052001 (2013)
116
Boston University, Boston, Massachusetts, USA
Brown University, Providence, Rhode Island, USA
118
University of California, Davis, Davis, California, USA
119
University of California, Los Angeles, California, USA
120
University of California, Riverside, Riverside, California, USA
121
University of California, San Diego, La Jolla, California, USA
122
University of California, Santa Barbara, Santa Barbara, California, USA
123
California Institute of Technology, Pasadena, California, USA
124
Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
125
University of Colorado at Boulder, Boulder, Colorado, USA
126
Cornell University, Ithaca, New York, USA
127
Fairfield University, Fairfield, Connecticut, USA
128
Fermi National Accelerator Laboratory, Batavia, Illinois, USA
129
University of Florida, Gainesville, Florida, USA
130
Florida International University, Miami, Florida, USA
131
Florida State University, Tallahassee, Florida, USA
132
Florida Institute of Technology, Melbourne, Florida, USA
133
University of Illinois at Chicago (UIC), Chicago, Illinois, USA
134
The University of Iowa, Iowa City, Iowa, USA
135
Johns Hopkins University, Baltimore, Maryland, USA
136
The University of Kansas, Lawrence, Kansas, USA
137
Kansas State University, Manhattan, Kansas, USA
138
Lawrence Livermore National Laboratory, Livermore, California, USA
139
University of Maryland, College Park, Maryland, USA
140
Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
141
University of Minnesota, Minneapolis, Minnesota, USA
142
University of Mississippi, Oxford, Mississippi, USA
143
University of Nebraska-Lincoln, Lincoln, Nebraska, USA
144
State University of New York at Buffalo, Buffalo, New York, USA
145
Northeastern University, Boston, Massachusetts, USA
146
Northwestern University, Evanston, Illinois, USA
147
University of Notre Dame, Notre Dame, Indiana, USA
148
The Ohio State University, Columbus, Ohio, USA
149
Princeton University, Princeton, New Jersey, USA
150
University of Puerto Rico, Mayaguez, Puerto Rico, USA
151
Purdue University, West Lafayette, Indiana, USA
152
Purdue University Calumet, Hammond, Indiana, USA
153
Rice University, Houston, Texas, USA
154
University of Rochester, Rochester, New York, USA
155
The Rockefeller University, New York, New York, USA
156
Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
157
University of Tennessee, Knoxville, Tennessee, USA
158
Texas A&M University, College Station, Texas, USA
159
Texas Tech University, Lubbock, Texas, USA
160
Vanderbilt University, Nashville, Tennessee, USA
161
University of Virginia, Charlottesville, Virginia, USA
162
Wayne State University, Detroit, Michigan, USA
163
University of Wisconsin, Madison, Wisconsin, USA
117
a
Deceased.
Also at Vienna University of Technology, Vienna, Austria.
c
Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland.
d
Also at Institut Pluridisciplinaire Hubert Curien, Université de Strasbourg, Université de Haute Alsace Mulhouse, CNRS/IN2P3,
Strasbourg, France.
e
Also at National Institute of Chemical Physics and Biophysics, Tallinn, Estonia.
f
Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia.
g
Also at Universidade Estadual de Campinas, Campinas, Brazil.
h
Also at California Institute of Technology, Pasadena, CA, USA.
i
Also at Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France.
j
Also at Suez Canal University, Suez, Egypt.
b
052001-20
MEASUREMENT OF NEUTRAL STRANGE PARTICLE . . .
k
PHYSICAL REVIEW D 88, 052001 (2013)
Also at Cairo University, Cairo, Egypt.
Also at Fayoum University, El-Fayoum, Egypt.
m
Also at Helwan University, Cairo, Egypt.
n
Also at British University in Egypt, Cairo, Egypt.
o
Now at Ain Shams University, Cairo, Egypt.
p
Also at National Centre for Nuclear Research, Swierk, Poland.
q
Also at Université de Haute Alsace, Mulhouse, France.
r
Also at Joint Institute for Nuclear Research, Dubna, Russia.
s
Also at Brandenburg University of Technology, Cottbus, Germany.
t
Also at The University of Kansas, Lawrence, KS, USA.
u
Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary.
v
Also at Eötvös Loránd University, Budapest, Hungary.
w
Also at Tata Institute of Fundamental Research-HECR, Mumbai, India.
x
Now at King Abdulaziz University, Jeddah, Saudi Arabia.
y
Also at University of Visva-Bharati, Santiniketan, India.
z
Also at University of Ruhuna, Matara, Sri Lanka.
aa
Also at Sharif University of Technology, Tehran, Iran.
bb
Also at Isfahan University of Technology, Isfahan, Iran.
cc
Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran.
dd
Also at Università degli Studi di Siena, Siena, Italy.
ee
Also at Universidad Michoacana de San Nicolas de Hidalgo, Morelia, Mexico.
ff
Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia.
gg
Also at Facoltà Ingegneria, Università di Roma, Roma, Italy.
hh
Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy.
ii
Also at INFN Sezione di Roma, Roma, Italy.
jj
Also at University of Athens, Athens, Greece.
kk
Also at Rutherford Appleton Laboratory, Didcot, United Kingdom.
ll
Also at Paul Scherrer Institut, Villigen, Switzerland.
mm
Also at Institute for Theoretical and Experimental Physics, Moscow, Russia.
nn
Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland.
oo
Also at Gaziosmanpasa University, Tokat, Turkey.
pp
Also at Adiyaman University, Adiyaman, Turkey.
qq
Also at Cag University, Mersin, Turkey.
rr
Also at Mersin University, Mersin, Turkey.
ss
Also at Izmir Institute of Technology, Izmir, Turkey.
tt
Also at Ozyegin University, Istanbul, Turkey.
uu
Also at Kafkas University, Kars, Turkey.
vv
Also at Suleyman Demirel University, Isparta, Turkey.
ww
Also at Ege University, Izmir, Turkey.
xx
Also at Mimar Sinan University, Istanbul, Istanbul, Turkey.
yy
Also at Kahramanmaras Sütcü Imam University, Kahramanmaras, Turkey.
zz
Also at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom.
aaa
Also at INFN Sezione di Perugia, Università di Perugia, Perugia, Italy.
bbb
Also at Utah Valley University, Orem, UT, USA.
ccc
Also at University of Edinburgh, Scotland, Edinburgh, United Kingdom.
ddd
Also at Institute for Nuclear Research, Moscow, Russia.
eee
Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia.
fff
Also at Argonne National Laboratory, Argonne, IL, USA.
ggg
Also at Erzincan University, Erzincan, Turkey.
hhh
Also at Yildiz Technical University, Istanbul, Turkey.
iii
Also at Kyungpook National University, Daegu, Korea.
l
052001-21